NYC restaurant week holds twice a year. During the time period, the price is only \(26\) on Lunch and \(42\) on Dinner with specially-offered two-course & three-course at participating restaurants.
In this dataset of 2018, I will present the visualizations to show the relationships between reviews, price range, and locations.
Geospatial Geospatial graph here shows the location of restaurant. When click the clustering or the individual target, more information of restaurant will show. The information includes the name, website, phone number and address.
Barplots Focuses on the percentage of counts of different five star levels. Three barplots are divided by price range, which shows no impact on the percentage of star
Lollipop The graph focuses on the average review scores of different restaurant type. Japanese and Korean foods have the highest score, while Chinese get the lowest. Scores which are higher than the average of all types will be head up, otherwise will be head down.
Radarplot The radarplot wants to find out if the price range will affect the review score of four types. The results show that lower price range will result in lower score.
Text graphs I picked three types: Chinese, Japanese and Korean and French. I evaluate the frequency of all words in description to find out the words to represent the restaurant type.
Time Series Time Series Data Source comes from NYC Open Data, which focuses on the inspections situations of each restaurant.